The objectives of this study were to develop a system linking hydrologic and water quality models considering the mechanisms of agricultural reservoir and paddy cultivation and to evaluate whether the developed system simulates hydrologic and water quality processes better than a hydrologic model that do not consider the mechanisms. The system consisted of Hydrological Simulation Program-Fortran (HSPF) as a watershed model, Module-based hydrologic Analysis System for Agricultural watersheds (MASA) as reservoir water balance model, and Chemical, Runoff and Erosion from Agricultural Management System-Paddy (CREAMS-PADDY) as a hydrologic and water quality model for paddy fields. This study carried out on the Seolseong-Cheon watershed in Icheon, and the water level and water quality had been monitored for two years at the outlet of the watershed. According to the results of this study, the performance of the simulation using HSPF-MASA-CREAMS-PADDY system was better than others, but they did not show a statistically significant difference. This seemed to be due to the uncertainty of the farming data and the water quality data of the reservoir. Therefore, if accurate input data for the system is obtained, HSPF-MASA-CREAMS-PADDY system could be used to model an agricultural watershed to obtain more realistic results. The results of this study could be utilized to the modeling of agricultural watersheds in Korea where paddy rice cultivation is dominant.

Universal Soil Loss Equation (USLE) has been widely used to estimate potential soil loss because USLE is a simple and reliable method. The rainfall erosivity factor (R factor) explains rainfall characteristics. R factors, cited in the Bulletin on the Survey of the Erosion of Topsoil of the Ministry of Environment in the Republic of Korea, are too outdated to represent current rainfall patterns in the Republic of Korea. Rainfall datasets at one minute intervals from 2013 to 2017 were collected from fifty rainfall gauge stations to update R factors considering current rainfall condition. The updated R factors in this study were compared to the previous R factors which were calculated using the data from 1973 to 1996. The coefficient of determination between the updated and the previous R factors shows 0.374, which means the correlation is not significant. Therefore, it was concluded that the previous R factors might not explain current rainfall conditions. The other remarkable result was that regression equations using annual rainfall data might be inappropriate to estimate reasonable R factors because the correlation between annual rainfall and the R factors was generally unsatisfy.

The result of examination of diagnostic method, which is composed of a combination of a thermal camera and a drone that visually shows the temperature of the object by detecting the infrared rays, for detecting the leakage of earth dam was driven in this research. The drone infrared thermography method was suggested to precise safety diagnosis through direct comparing the two method results of electrical resistivity survey and thermal image survey. The important advantage of the thermal leakage detection method was the simplicity of the application, the quickness of the results, and the effectiveness of the work in combination with the existing diagnosis method.

This study evaluated the vulnerability of irrigation water supplied to the crops. The target areas were selected as Dangjin-si, Yesan-gun, and Cheongyang-gun. The survey items of the climate exposure were annual precipitation and rainless days. The sensitivity survey items were cultivation area, groundwater level, evapotranspiration and groundwater consumption. The survey items of the adaptability were Number of groundwater well and Water supply ratio. The survey methods for these items were investigated in a variety of ways, including “National Climate Data Service System”, “Korean Statistical Information Service”, “National ground water monitoring network in korea annual report” and “Chungcheongnam-do Statistical Yearbook”, “HOMWRS”. Vulnerability assessment results were rated within the range of 0∼100 points. The first grade was rated 0-25, the second grade 26-50, the third grade 51-75, and the fourth grade 76-100. And the lower the score, the lower the vulnerability. As a result, Cheongyang-gun showed a high vulnerability of over 50 points, Dangjin-si showed a low vulnerability rating of 31.20 points and a Yesan-gun of 36.00 points.

The accurate estimation of reference crop evapotranspiration (ETo) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of ETo has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict ETo using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily ETo was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of ETo and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against ETo calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

This paper aimed to characterize the spatial and temporal pattern of agricultural drought in Pre-Kharif season using Vegetation Health Index (VHI) and illustrated drought characteristics in Bangladesh during 2001-2015. VHI was calculated from TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS Terra satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The finding showed that all drought-affected areas were experienced by mild, moderate, severe and extreme droughts in several years of Pre-Kharif seasons. Significant drought events were found in the year of 2002 and 2013. On average, Chittagong district covered the largest drought area in all drought stages, and the fraction of drought area was the highest in Sylhet and Rangpur for Pre-Kharif season. Finally, overlaying annual VHI raster maps resulted in that the most vulnerable district to agricultural drought were Sylhet, Rangpur, and Mymensingh in the northern and eastern regions of Bangladesh.

The Long-Term Hydrologic Impact Assessment (L-THIA) model is a quick and straightforward analysis tool to estimate direct runoff and nonpoint source pollution. L-THIA was originally implemented as a spreadsheet application. GIS-based versions of L-THIA have been developed in ArcView 3 and upgraded to ArcGIS 9. However, a major upgrade was required for L-THIA to operate in the current version of ArcGIS and to provide more options in runoff and NPS estimation. An updated L-THIA interfaced with ArcGIS 10.0 and 10.1 has been developed in the study as an ArcGIS Desktop Tool. The model provides a user-friendly interface, easy access to the model parameters, and an automated watershed delineation process. The model allows use of precipitation data from multiple gauge locations for the watershed when a watershed is large enough to have more than one precipitation gauge station. The model estimated annual direct runoff well for our study area compared to separated direct runoff in the calibration and validation periods of ten and nine years. The ArcL-THIA, with a user-friendly interface and enhanced functions, is expected to be a decision support model requiring less effort for GIS processes or to be a useful educational hydrology model.

Comparative Study on the Subsurface Drainage Discharge Performance by the Type of Non-Excavation Subsurface Drainage Culvert

김현태 Kim Hyuntai , 유전용 Ryu Jeonyong , 정기열 Jung Kiyuol , 서동욱 Seo Donguk

DOI:10.5389/KSAE.2018.60.6.073 JKWST Vol.60(No.6) 73-81, 2018

In this study, subsurface discharge performance has been studied through theoretical seepage analysis on four types of culverts that can be installed under the condition of non-excavation, such as ⓐperforated pipe(Φ50mm), ⓑperforated pipe+horizontal mat (B50cm) ⓒperforated pipe+horizontal mat+vertical gravel(B<10cm), ⓓperforated pipe+vertical gravel(B<10cm), and existing typical type ⓔperforated pipe with gravel (B40, h=40cm) which can be installed by excavation. The analysis results were as follows. i) Subsurface discharge performance per unit (m) was ⓐtype 56%, ⓑ 91%, ⓒ 96%, ⓓ 76%, respectively, lower than the value of ⓔculvert. ii) However, considering that non-excavation culvert can be installed at a spacing of 5m with the installation cost of the existing excavation culvert at the interval of 10m, it was analyzed that unit subsurface discharge(q) of ⓐ20.2mm/day(110%), ⓑ32.8(178%), ⓒ34.6(188%) ⓓ27.5(149%) in the four types of non-excavation culvert installed at intervals of 5m under the condition of k=10-4cm/s was much larger than the amount of ⓔtype 18.5(100%), existing excavation culvert installed at 10m interval. iii) Through the test construction, peak subsurface drainage discharge(qp) was 38.4mm/day, which is larger than the value of design criteria and confirmed that it satisfies the analysis results as well. iv) In particular, it was evaluated that ⓑperforated pipe+horizontal mat(B50cm) are low cost, high efficiency subsurface drainage culvert type with sufficient drainage performance(178%).

The objective of this study was to estimate the climate change impact on water quantity and quality to Saemanguem watershed using SWAT (Soil and water assessment tool) model. The SWAT model was calibrated and validated using observed data from 2008 to 2017 for the study watershed. The R2 (Determination coefficient), RMSE (Root mean square error), and NSE (Nash-sutcliffe efficiency coefficient) were used to evaluate the model performance. RCP scenario data were produced from 10 GCM (General circulation model) and all relevant grid data including the major observation points (Gusan, Jeonju, Buan, Jeongeup) were extracted. The systematic error evaluation of the GCM model outputs was performed as well. They showed various variations based on analysis of future climate change effects. In future periods, the MIROC5 model showed the maximum values and the CMCC-CM model presented the minimum values in the climate data. Increasing rainfall amount was from 180mm to 250mm and increasing temperature value ranged from 1.7 to 5.9℃, respectively, compared with the baseline (2006∼2017) in 10 GCM model outputs. The future 2030s and 2070s runoff showed increasing rate of 16∼29% under future climate data. The future rate of change for T-N (Total nitrogen) and T-P (Total phosphorus) loads presented from -26 to +0.13% and from +5 to 47%, respectively. The hydrologic cycle and water quality from the Saemanguem headwater were very sensitive to projected climate change scenarios so that GCM model should be carefully selected for the purpose of use and the tendency analysis of GCM model are needed if necessary.

The LDC (Load Duration Curve) method can analyze river water quality changes according to flow rate and seasonal conditions. It is also possible to visually recognize whether the target water quality is exceeded or the size of the reduction load. For this reason, it is used for the optimal reduction of TPLCs and analysis of the cause of water pollution. At this time, the flow duration curve should be representative of the water body hydrologic curve, but if not, the uncertainty of the interpretation becomes big because the damaged flow condition is changed. The purpose of this study is to estimate the daily mean flow of the unit watershed using the HSPF model and to analyze the difference of the flow duration curves according to the cumulative daily mean flow rate using the NSE technique. The results show that it is desirable to construct the flow duration curve by using the daily average flow rate of at least 5 years although there is a difference by unit watershed. However, this is the result of the water bodies at the end of Han River basin watershed, so further study on various water bodies will be necessary in the future.